This is a working document for all the coral physiology data manipulation, analysis, and visualization of the physiology manuscript. The document includes all figures, tables, supplemental materials, methods, and results for the manuscript. Each major analysis is separated by the tabs on the left.



Principal component analyses

Methods:

Principal component analysis (PCA) (function prcomp) of scaled and centered physiological parameters (host carbohydrate, host lipid, host protein, algal endosymbiont chlorophyll a, algal endosymbiont cell density, holobiont calcification rate as previously for the same samples in Bove et al. (2019)) were employed to assess the relationship between physiological parameters and treatment conditions for each coral species. Main effects (temperature, pCO2, and reef environment) were evaluated with PERMANOVA using the adonis2 function (vegan package; version 2.5.7). An additional PERMANOVA was conducted on the combined physiology from all three species to compare species responses combined with treatments and reef environment.


Siderastrea siderea

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F    Pr(>F)    
## fpco2     3    61072 0.20845 8.1535 0.0006662 ***
## ftemp     1     7471 0.02550 2.9922 0.0872751 .  
## reef      1    24705 0.08432 9.8948 0.0019987 ** 
## Residual 80   199740 0.68174                     
## Total    85   292988 1.00000                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Pseudodiploria strigosa

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df ~ reef + ftemp + fpco2, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1    97850 0.08659 14.2890 0.0006662 ***
## ftemp     1   515604 0.45625 75.2935 0.0006662 ***
## fpco2     3    30444 0.02694  1.4819 0.2591606    
## Residual 71   486202 0.43023                      
## Total    76  1130099 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Porites astreoides

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df ~ reef + ftemp + fpco2, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## reef      1      157 0.00111  0.1138 0.7601599    
## ftemp     1    25414 0.17971 18.4700 0.0006662 ***
## fpco2     3    30537 0.21594  7.3978 0.0013324 ** 
## Residual 62    85309 0.60325                      
## Total    67   141417 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Figure 1

Figure 1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides after 93 days of exposure to different temperature and pCO2 treatments. PCAs in the top row are depicted by temperature treatment for each species (28\(^\circ\) C blue; 31\(^\circ\) C red) and the bottom row of PCAs are depicted by pCO2 for each species (300 \(\mu\)atm light purple; 420 \(\mu\)atm dark purple; 680 \(\mu\)atm light orange; 3290 \(\mu\)atm dark orange). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure 4

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = all_pca_df ~ fpco2 + ftemp + reef + species + ftemp:species + fpco2:species + reef:species, data = all_df, permutations = bootnum, method = "eu")
##                Df SumOfSqs      R2        F    Pr(>F)    
## fpco2           3   149393 0.03848   8.2405 0.0006662 ***
## ftemp           1    17313 0.00446   2.8650 0.0919387 .  
## reef            1    58058 0.01496   9.6075 0.0039973 ** 
## species         2  1642613 0.42313 135.9102 0.0006662 ***
## ftemp:species   2   553351 0.14254  45.7844 0.0006662 ***
## fpco2:species   6    90865 0.02341   2.5061 0.0173218 *  
## reef:species    2    77259 0.01990   6.3924 0.0046636 ** 
## Residual      214  1293204 0.33312                       
## Total         231  3882055 1.00000                       
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure 4. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted by (A) species, (B) pCO2 treatment, and (C) temperature treatment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Results

Principal component analysis

Two principal components (PCs) explained approximately 66% of the variance in physiological responses of the S. siderea holobiont to ocean acidification and warming treatments (Figure 1A). PC1 was driven by differences in algal symbiont physiology (chlorophyll a, cell density), while PC2 represented an inverse relationship between host energy reserves (lipid, protein, carbohydrate) and calcification rates and color intensities. Overall, lower pCO2 and temperature resulted in higher S. siderea holobiont physiology (Figure 1A). Treatment pCO2 predominantly drove S. siderea physiological responses (p = 7e-04; Table S2), while temperature and reef environment did not explain as much variation in physiological responses (p = 0.09 and p = 0.002, respectively; Table S2; Figure S1A).

For P. strigosa, 74% of the variance in the holobiont responses to treatments was explained by two PCs (Figure 1B). PC1 explained most of the variation of physiological parameters with the exception of host lipid content, which was represented in PC2. Holobiont physiology of P. strigosa was reduced under warming (p = 7e-04; Table S2) and in offshore samples (p = 7e-04; Table S2; Figure S1B), however, pCO2 did not clearly impact holobiont physiology (Figure 1B; p = 0.3; Table S2).

For P. astreoides, the first two PCs explained about 59% of the total variance in holobiont response to treatment (Figure 1C). Samples separated most clearly along PC1 driven primarily by calcification rate and algal symbiont density, while PC2 exhibited an inverse relationship between host total carbohydrate and color intensity. Overall, lower pCO2 drove higher P. astreoides holobiont physiology, while elevated temperature resulted in greater holobiont physiology (Figure 1C). Temperature (p = 7e-04; Table S2) and pCO2 (p = 0.001; Table S2) clearly altered P. astreoides holobiont physiology, while reef environment was not significant (p = 0.8; Table S2; Figure S1C).


Species differences in coral holobiont physiology

The first two PCs of the combined holobiont physiology explained about 62% of the total variance across samples (Figure 4). In general, fragments of S. siderea contained higher chlorophyll a content, host carbohydrate, and host lipid content, while P. strigosa fragments typically had greater host protein content accompanied by higher calcification rates, and fragments of P. astreoides were differentiated by their high symbiont densities (Figure 4A; Table S5). Despite being different coral species, coral holobiont physiology exhibited similar physiological responses to pCO2 and temperature treatments (Figure 4B, 4C; Table S5). As pCO2 or temperature increased, coral holobiont physiology was more constrained and exhibited convergent physiological responses under stress. Furthermore, corals from the inshore reef environment exhibited more constrained physiology than their offshore counterparts (Figure S7; Table S5).



Correlation assessments

Methods:

Correlations of all physiological parameters were assessed to determine the relationships between parameters within each species, redargless of temperature and pCO2 treatment. The Pearson correlation coefficient (R2) of each comparison was calculated using the corrgram package (version 1.13) and the significance was calculated using the cor.test function. These relationships were then visualized through simple scatterplots.


Figure 2

Figure 2. Coral holobiont correlation matrices (bottom panel) and scatter plots (top panel) for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides depicting pairwise comparisons of physiological parameters within each species. Strength of correlations between parameters is indicated by darker shades of blue in the bottom panel with a higher R2 value (Pearson correlation coefficient). Of these correlations, significant correlations are depicted with asterisks according to significance level (* p < 0.05; ** p < 0.01; *** p < 0.001). Scatter plots of physiological parameters are displayed in the top panel with temperature depicted by shape (28\(^\circ\)C filled points; 31\(^\circ\)C open points) and pCO2 depicted by color (300 \(\mu\)atm light purple; 420 \(\mu\)atm dark purple; 680 \(\mu\)atm light orange; 3290 \(\mu\)atm dark orange).



Results:

Correlations of physiological parameters

Correlations of coral holobiont physiological parameters were generally positively related with one another across all three species. Correlations between S. siderea holobiont physiological parameters identified 15 significant relationships out of all 21 possible comparisons (Figure 2A). Of those significant correlations, six resulted in a Pearson’s correlation coefficient (R2) equal to or greater than 0.5, with the strongest relationship identified being symbiont density vs chlorophyll a (R2 = 0.72). All pairwise physiological parameters were significantly correlated with one another in P. strigosa and of those, 14 correlations exhibit moderate (R2 > 0.50) positive relationships (Figure 2B). Notably, the two strongest correlations were host carbohydrate vs host protein (R2 = 0.70) and host carbohydrate vs chlorophyll a (R2 = 0.76). Compared to both S. siderea and P. strigosa, fewer physiological traits were significantly (p < 0.05) correlated with one another in P. astreoides (12 significant out of 21 total comparisons; Figure 2C). Of the significant correlations, only two pairwise comparisons resulted in a Pearson’s correlation coefficient greater than 0.5: chlorophyll a vs color intensity (R2 = 0.57) and host carbohydrate vs host protein (R2 = 0.68).



Plasticity analyses

Methods:

Using PC1 and PC2 for each species, we then calculated the physiological plasticity of each experimental fragment. Plasticity was calculated as the PC distance between an experimental fragment and the control (420 \(\mu\)atm; 28\(^\circ\)C) fragment from that same colony. The effects of treatment (pCO2 and temperature) and natal reef environment on calculated distances were assessed using generalized linear models (function glm) with a Gamma distribution and log-link. The best-fit model was selected as the model with the lowest AIC for each species (Table S1). The main effects of treatment and reef environment were assessed with an ANOVA (package car; version 3.0.10) with a type III error. All figures and statistical analyses were carried out in R version 3.6.3 (R Core Development Team 2016).


Siderastrea siderea

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: Gamma  ( log )
## Formula: dist ~ reef * fpco2 + ftemp + (1 | colony)
##    Data: sid_dist
## 
##      AIC      BIC   logLik deviance df.resid 
##    218.8    243.5    -98.4    196.8       59 
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -1.99957 -0.62958 -0.09185  0.40989  2.93911 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  colony   (Intercept) 0.03567  0.1889  
##  Residual             0.09609  0.3100  
## Number of obs: 70, groups:  colony, 11
## 
## Fixed effects:
##                  Estimate Std. Error t value Pr(>|z|)    
## (Intercept)      1.085047   0.172255   6.299 2.99e-10 ***
## reefN           -0.058293   0.247860  -0.235  0.81406    
## fpco2420         0.334631   0.172672   1.938  0.05263 .  
## fpco2680         0.209598   0.130838   1.602  0.10916    
## fpco23290        0.418697   0.132009   3.172  0.00152 ** 
## ftemp31          0.003138   0.076026   0.041  0.96708    
## reefN:fpco2420  -0.703806   0.238723  -2.948  0.00320 ** 
## reefN:fpco2680  -0.409193   0.196622  -2.081  0.03742 *  
## reefN:fpco23290 -0.278200   0.191371  -1.454  0.14602    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) reefN  fp2420 fp2680 f23290 ftmp31 rN:242 rN:268
## reefN       -0.671                                                 
## fpco2420    -0.304  0.252                                          
## fpco2680    -0.459  0.325  0.468                                   
## fpco23290   -0.446  0.320  0.475  0.611                            
## ftemp31     -0.159 -0.038 -0.275 -0.041 -0.069                     
## rfN:fpc2420  0.244 -0.352 -0.678 -0.331 -0.331  0.034              
## rfN:fpc2680  0.310 -0.438 -0.303 -0.664 -0.404 -0.004  0.456       
## rfN:fp23290  0.309 -0.449 -0.324 -0.421 -0.689  0.035  0.466  0.572



Pseudodiploria strigosa

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: Gamma  ( log )
## Formula: dist ~ fpco2 + ftemp + (1 | colony)
##    Data: dip_dist
## 
##      AIC      BIC   logLik deviance df.resid 
##    102.8    111.6    -44.4     88.8       19 
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -1.73343 -0.69994  0.02543  0.73391  2.05176 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  colony   (Intercept) 0.007871 0.08872 
##  Residual             0.132559 0.36409 
## Number of obs: 26, groups:  colony, 5
## 
## Fixed effects:
##             Estimate Std. Error t value Pr(>|z|)    
## (Intercept)  1.27928    0.14529   8.805   <2e-16 ***
## fpco2420     0.19425    0.41845   0.464   0.6425    
## fpco2680    -0.33877    0.18965  -1.786   0.0741 .  
## fpco23290   -0.05963    0.18390  -0.324   0.7457    
## ftemp31      0.22591    0.16969   1.331   0.1831    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##           (Intr) fp2420 fp2680 f23290
## fpco2420  -0.167                     
## fpco2680  -0.577  0.183              
## fpco23290 -0.576  0.204  0.484       
## ftemp31   -0.333 -0.274  0.067  0.014



Porites astreoides

## Generalized linear mixed model fit by maximum likelihood (Laplace
##   Approximation) [glmerMod]
##  Family: Gamma  ( log )
## Formula: dist ~ fpco2 + ftemp + (1 | colony)
##    Data: por_dist
## 
##      AIC      BIC   logLik deviance df.resid 
##    140.4    154.4    -63.2    126.4       47 
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.6588 -0.5857 -0.1014  0.5424  2.2086 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  colony   (Intercept) 0.03732  0.1932  
##  Residual             0.05675  0.2382  
## Number of obs: 54, groups:  colony, 11
## 
## Fixed effects:
##             Estimate Std. Error t value Pr(>|z|)    
## (Intercept)  1.03836    0.12055   8.613  < 2e-16 ***
## fpco2420    -0.04691    0.11022  -0.426    0.670    
## fpco2680     0.03247    0.07465   0.435    0.664    
## fpco23290    0.12169    0.07752   1.570    0.116    
## ftemp31      0.26414    0.06483   4.074 4.62e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##           (Intr) fp2420 fp2680 f23290
## fpco2420  -0.138                     
## fpco2680  -0.313  0.383              
## fpco23290 -0.330  0.294  0.529       
## ftemp31   -0.176 -0.379 -0.087  0.089



Figure 3

Figure 3. Assessment of physiological plasticity of (A) S. siderea, (B) P. strigosa, and (C) P. astreoides in experimental treatments and by natal reef environment. Higher values represent greater plasticity in coral holobiont samples. pCO2 treatment is depicted by color and shape (300 \(\mu\)atm light purple, circle; 420 \(\mu\)atm dark purple, diamond; 680 \(\mu\)atm light orange, triangle; 3290 \(\mu\)atm dark orange, square) and temperature is represented as either filled (28\(^\circ\)C) or open (31\(^\circ\)C) symbols.



Results:

Natal reef environment (p < 0.05) and pCO2 (p < 0.05) significantly altered the physiological plasticity of S. siderea (Figure 3A; Table S3, S4). Offshore fragments exhibited a positive linear trend with increasing pCO2 while the inshore fragments appear to respond in a parabolic pattern to pCO2, with the lowest calculated distances occurring at 420 \(\mu\)atm, 31\(^\circ\)C and 680 \(\mu\)atm, 28\(^\circ\)C. Plasticity of P. strigosa and P. astreoides was not significantly altered by temperature treatment, pCO2 treatment, or natal reef environment (Figure 3B, 3C; Table S3, S4). However, P. astreoides exhibited a slight trend in the inshore fragments suggesting potentially higher plasticity with increasing pCO2 that is not seen in the offshore fragments (Figure 3C).



Supplemental Figures

Figure S1

Figure S1. Principal component analysis (PCA) of all coral holobiont physiological parameters for (A) S. siderea, (B) P. strigosa, and (C) P. astreoides depicted by natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S2

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df_host ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F   Pr(>F)   
## fpco2     3    0.627 0.01852 0.5482 0.748834   
## ftemp     1    2.533 0.07483 6.6463 0.003997 **
## reef      1    0.199 0.00589 0.5229 0.582945   
## Residual 80   30.485 0.90076                   
## Total    85   33.844 1.00000                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = sid_pca_df_symb ~ fpco2 + ftemp + reef, data = s_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F    Pr(>F)    
## fpco2     3    61056 0.20844 8.1537 0.0006662 ***
## ftemp     1     7468 0.02550 2.9920 0.0846103 .  
## reef      1    24705 0.08434 9.8975 0.0019987 ** 
## Residual 80   199684 0.68172                     
## Total    85   292913 1.00000                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S2. Principal component analysis (PCA) of S. siderea coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S3

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df_host ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3   0.7317 0.04116  1.2287 0.2871419    
## ftemp     1   2.6047 0.14652 13.1213 0.0006662 ***
## reef      1   0.3469 0.01952  1.7478 0.1592272    
## Residual 71  14.0939 0.79281                      
## Total    76  17.7772 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = dip_pca_df_symb ~ fpco2 + ftemp + reef, data = p_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3    26899 0.02380  1.3095 0.2778148    
## ftemp     1   515173 0.45590 75.2402 0.0006662 ***
## reef      1   101793 0.09008 14.8666 0.0006662 ***
## Residual 71   486140 0.43021                      
## Total    76  1130005 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S3. Principal component analysis (PCA) of P. strigosa coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S4

## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df_host ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2      F  Pr(>F)  
## fpco2     3   1.7463 0.13595 3.4824 0.01865 *
## ftemp     1   0.4610 0.03589 2.7580 0.10060  
## reef      1   0.2740 0.02133 1.6394 0.20053  
## Residual 62  10.3638 0.80682                 
## Total    67  12.8452 1.00000                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation test for adonis under reduced model
## Terms added sequentially (first to last)
## Permutation: free
## Number of permutations: 1500
## 
## adonis2(formula = por_pca_df_symb ~ fpco2 + ftemp + reef, data = a_df, permutations = bootnum, method = "eu")
##          Df SumOfSqs      R2       F    Pr(>F)    
## fpco2     3    29037 0.20537  7.0360 0.0006662 ***
## ftemp     1    26338 0.18628 19.1461 0.0006662 ***
## reef      1      724 0.00512  0.5263 0.4816789    
## Residual 62    85288 0.60323                      
## Total    67   141387 1.00000                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Figure S4. Principal component analysis (PCA) of P. asteroides coral host (protein, lipid, carbohydrate; left) or algal symbiont (chlorophyll a, symbiont density, color intensity; right) physiological parameters by temperature (28 °C blue; 31 °C red), pCO2 (300 μatm light purple; 420 μatm dark purple; 680 μatm light orange; 3290 μatm dark orange), and natal reef environment (offshore green; inshore yellow). Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S5

Figure S5. Mean (\(\pm\)SE) physiological parameter (each row) measured for (A) S. siderea, (B) P. strigosa, (C) P. astreoides, and (D) U. tenuifolia at the completion of the 93-day experimental period.



Figure S6

Figure S6. Coral color changes over the experimental period. Representative images of fragments of (A) P. astreoides, (B) S. siderea, and (C) P. strigosa from the same colonies demonstrating change in coral color over time in either control (420 μatm; 28 °C) or warming (420 μatm; 31 °C) treatments from the start of the experiment (T0) to the end (T90).



Figure S7

Figure S7. Principal component analysis (PCA) comparing the coral holobiont of all three species at the end of the experiment depicted reef environment. Arrows represent significant (p < 0.05) correlation vectors for physiological parameters and ellipses represent 95% confidence based on multivariate t-distributions.



Figure S8



Supplemental Tables

Table S1

Table S1. Model performance comparisons of generalized linear models (GLM) for plasticity assessments to select the best-fit model per species using the package performance (version 0.7.0). Akaike information criterion (AIC) was used to select the best-fit model per species. The performance score computes indices of model performance for all models per species at once for comparison across models.
Model formula AIC BIC Conditional R2 Marginal R2
Siderastrea Siderea
reef environment * pCO2 + temperature + (1 | colony) 218.8 243.5 0.5059 0.3225
reef environment * pCO2 * temperature + (1 | colony) 223.2 259.2 0.5445 0.3656
reef environment * (pCO2 + temperature) + (1 | colony) 220.1 247.1 0.5115 0.3288
reef environment + pCO2 + temperature + (1 | colony) 221.6 239.6 0.4419 0.2535
pCO2 + temperature + (1 | colony) 222.1 237.8 0.3698 0.0882
reef environment + pCO2 * temperature + (1 | colony) 225.6 248.1 0.4421 0.2534
Pseudodiploria strigosa
reef environment * pCO2 * temperature + (1 | colony) 110.7 128.3 0.4274 0.3474
reef environment * pCO2 + temperature + (1 | colony) 106.0 118.6 0.3408 0.2916
reef environment + pCO2 * temperature + (1 | colony) 106.9 119.5 0.3131 0.2714
pCO2 + temperature + (1 | colony) 102.8 111.6 0.2678 0.2243
Porites astreoides
reef environment * pCO2 + temperature + (1 | colony) 145.9 167.8 0.5212 0.1950
reef environment * (pCO2 + temperature) + (1 | colony) 147.9 171.8 0.5217 0.1952
reef environment * pCO2 * temperature + (1 | colony) 153.1 182.9 0.5273 0.1994
reef environment + pCO2 + temperature + (1 | colony) 142.3 158.2 0.4988 0.1738
pCO2 + temperature + (1 | colony) 140.4 154.4 0.4853 0.1469
reef environment + pCO2 * temperature + (1 | colony) 146.2 166.1 0.4995 0.1741




Table S2

Table S2. PERMANOVA model output from each species using the adonis2 function with 1500 iterations.
Df Sum of Squares R2 F P-value
Siderastrea Siderea
pCO2 3 61072 0.208 8.15 0.00067
temperature 1 7471 0.025 2.99 0.08728
reef environment 1 24705 0.084 9.89 0.00200
Residual 80 199740 0.682
Total 85 292988 1.000
Pseudodiploria strigosa
reef environment 1 97850 0.087 14.29 0.00067
temperature 1 515604 0.456 75.29 0.00067
pCO2 3 30444 0.027 1.48 0.25916
Residual 71 486202 0.430
Total 76 1130099 1.000
Porites astreoides
reef environment 1 157 0.001 0.11 0.76016
temperature 1 25414 0.180 18.47 0.00067
pCO2 3 30537 0.216 7.40 0.00133
Residual 62 85309 0.603
Total 67 141417 1.000




Table S3

Table S3. GLMM output from plasticity assessments for each species. The intercept of each model was set as 300 \(\mu\)atm, 28\(^\circ\)C, and inshore reef environment.
Estimate Standard error Statistic P-value
Siderastrea Siderea
Intercept 1.085 0.172 6.30 0.000
reef environment (offshore) -0.058 0.248 -0.24 0.814
pCO2 0.335 0.173 1.94 0.053
pCO2 0.210 0.131 1.60 0.109
pCO2-extreme 0.419 0.132 3.17 0.002
temperature (31C) 0.003 0.076 0.04 0.967
reef environment (offshore) pCO2 -0.704 0.239 -2.95 0.003
reef environment (offshore) pCO2 -0.409 0.197 -2.08 0.037
reef environment (offshore) pCO2-extreme -0.278 0.191 -1.45 0.146
Pseudodiploria strigosa
Intercept 1.279 0.145 8.80 0.000
pCO2 0.194 0.418 0.46 0.643
pCO2 -0.339 0.190 -1.79 0.074
pCO2-extreme -0.060 0.184 -0.32 0.746
temperature (31C) 0.226 0.170 1.33 0.183
Porites astreoides
Intercept 1.038 0.121 8.61 0.000
pCO2 -0.047 0.110 -0.43 0.670
pCO2 0.032 0.075 0.44 0.664
pCO2-extreme 0.122 0.078 1.57 0.116
temperature (31C) 0.264 0.065 4.07 0.000




Table S4

Table S4. PERMANOVA model output across species using the adonis2 function with 1500 iterations.
Df Sum of Squares R2 F P-value
pCO2 3 149393 0.038 8.24 0.00067
temperature 1 17313 0.004 2.87 0.09194
reef environment 1 58058 0.015 9.61 0.00400
species 2 1642613 0.423 135.91 0.00067
temperature:species 2 553351 0.143 45.78 0.00067
pCO2:species 6 90865 0.023 2.51 0.01732
reef environment:species 2 77259 0.020 6.39 0.00466
Residual 214 1293204 0.333
Total 231 3882055 1.000




Table S5

Table S5. PERMANOVA model output of coral host or algal symbiont physiology per species using the adonis2 function with 1500 iterations depicted in Figures S2-S4.
Coral host
Algal symbionts
Df Sum of Squares R2 F P-value Df Sum of Squares R2 F P-value
Siderastrea Siderea
pCO2 3 1 0.019 0.55 0.74883 3 61056 0.208 8.15 0.00067
temperature 1 3 0.075 6.65 0.00400 1 7468 0.025 2.99 0.08461
reef environment 1 0 0.006 0.52 0.58294 1 24705 0.084 9.90 0.00200
Residual 80 30 0.901 80 199684 0.682
Total 85 34 1.000 85 292913 1.000
Pseudodiploria strigosa
pCO2 3 1 0.041 1.23 0.28714 3 26899 0.024 1.31 0.27781
temperature 1 3 0.147 13.12 0.00067 1 515173 0.456 75.24 0.00067
reef environment 1 0 0.020 1.75 0.15923 1 101793 0.090 14.87 0.00067
Residual 71 14 0.793 71 486140 0.430
Total 76 18 1.000 76 1130005 1.000
Porites astreoides
pCO2 3 2 0.136 3.48 0.01865 3 29037 0.205 7.04 0.00067
temperature 1 0 0.036 2.76 0.10060 1 26338 0.186 19.15 0.00067
reef environment 1 0 0.021 1.64 0.20053 1 724 0.005 0.53 0.48168
Residual 62 10 0.807 62 85288 0.603
Total 67 13 1.000 67 141387 1.000




Session information

Session information from the last run date on 2021-06-28:

## R version 3.6.3 (2020-02-29)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Catalina 10.15.7
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] rcompanion_2.4.1      car_3.0-10            carData_3.0-4        
##  [4] png_0.1-7             MASS_7.3-53           performance_0.7.0    
##  [7] wesanderson_0.3.6     RColorBrewer_1.1-2    gridGraphics_0.5-1   
## [10] corrplot_0.84         Hmisc_4.4-2           Formula_1.2-4        
## [13] survival_3.2-7        magick_2.5.2          ggpubr_0.4.0         
## [16] vroom_1.3.2           lmerTest_3.1-3        lme4_1.1-26          
## [19] Matrix_1.3-2          kableExtra_1.3.1      finalfit_1.0.2       
## [22] ggfortify_0.4.11-9009 cowplot_1.1.1         Rmisc_1.5            
## [25] shiny_1.5.0           vegan_2.5-7           lattice_0.20-41      
## [28] permute_0.9-5         forcats_0.5.0         stringr_1.4.0        
## [31] purrr_0.3.4           tibble_3.0.4          tidyverse_1.3.0      
## [34] plotly_4.9.3          openxlsx_4.2.3        corrgram_1.13        
## [37] tidyr_1.1.2           ggbiplot_0.55         scales_1.1.1         
## [40] plyr_1.8.6            dplyr_1.0.2           ggplot2_3.3.3        
## [43] broom_0.7.3           readr_1.4.0           knitr_1.33           
## 
## loaded via a namespace (and not attached):
##   [1] tidyselect_1.1.0    htmlwidgets_1.5.3   TSP_1.1-10         
##   [4] munsell_0.5.0       codetools_0.2-18    effectsize_0.4.1   
##   [7] statmod_1.4.35      withr_2.4.2         colorspace_2.0-0   
##  [10] highr_0.8           rstudioapi_0.13     stats4_3.6.3       
##  [13] DescTools_0.99.41   ggsignif_0.6.0      labeling_0.4.2     
##  [16] bit64_4.0.5         farver_2.0.3        vctrs_0.3.6        
##  [19] generics_0.1.0      TH.data_1.0-10      xfun_0.22          
##  [22] R6_2.5.0            seriation_1.2-9     assertthat_0.2.1   
##  [25] promises_1.1.1      multcomp_1.4-15     nnet_7.3-14        
##  [28] rootSolve_1.8.2.1   gtable_0.3.0        multcompView_0.1-8 
##  [31] lmom_2.8            sandwich_3.0-0      rlang_0.4.11       
##  [34] splines_3.6.3       rstatix_0.6.0       lazyeval_0.2.2     
##  [37] checkmate_2.0.0     yaml_2.2.1          abind_1.4-5        
##  [40] modelr_0.1.8        backports_1.2.1     httpuv_1.5.5       
##  [43] tools_3.6.3         ellipsis_0.3.1      ggridges_0.5.3     
##  [46] Rcpp_1.0.5          base64enc_0.1-3     rpart_4.1-15       
##  [49] zoo_1.8-8           haven_2.3.1         ggrepel_0.9.0      
##  [52] cluster_2.1.0       fs_1.5.0            magrittr_2.0.1     
##  [55] data.table_1.13.6   lmtest_0.9-38       reprex_0.3.0       
##  [58] mvtnorm_1.1-1       matrixStats_0.57.0  hms_1.0.0          
##  [61] mime_0.10           evaluate_0.14       xtable_1.8-4       
##  [64] rio_0.5.16          jpeg_0.1-8.1        readxl_1.3.1       
##  [67] gridExtra_2.3       compiler_3.6.3      mice_3.13.0        
##  [70] crayon_1.3.4        minqa_1.2.4         htmltools_0.5.1    
##  [73] mgcv_1.8-33         later_1.1.0.1       libcoin_1.0-8      
##  [76] expm_0.999-6        Exact_2.1           lubridate_1.7.9.2  
##  [79] DBI_1.1.0           dbplyr_2.0.0        see_0.6.2          
##  [82] boot_1.3-25         cli_2.5.0           parallel_3.6.3     
##  [85] insight_0.13.1      pkgconfig_2.0.3     registry_0.5-1     
##  [88] numDeriv_2016.8-1.1 coin_1.4-1          foreign_0.8-75     
##  [91] xml2_1.3.2          foreach_1.5.1       webshot_0.5.2      
##  [94] rvest_0.3.6         digest_0.6.27       parameters_0.10.1  
##  [97] rmarkdown_2.6       cellranger_1.1.0    htmlTable_2.1.0    
## [100] nortest_1.0-4       gld_2.6.2           curl_4.3.1         
## [103] modeltools_0.2-23   nloptr_1.2.2.2      lifecycle_1.0.0    
## [106] nlme_3.1-151        jsonlite_1.7.2      viridisLite_0.3.0  
## [109] pillar_1.4.7        fastmap_1.0.1       httr_1.4.2         
## [112] glue_1.4.2          bayestestR_0.8.0    zip_2.1.1          
## [115] iterators_1.0.13    bit_4.0.4           class_7.3-17       
## [118] stringi_1.5.3       latticeExtra_0.6-29 e1071_1.7-4